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Buffer Sizing to Reduce Interference and Increase Throughput of Real-Time Stream Processing Applications

机译:缓冲区大小可减少干扰并提高实时流处理应用程序的吞吐量

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Existing temporal analysis and buffer sizing techniques for real-time stream processing applications ignore that FIFO buffers bound interference between tasks on the same processor. By considering this effect it can be shown that a reduction of buffer capacities can result in a higher throughput. However, the relation between buffer capacities and throughput is non-monotone in general, which makes an exploitation of the effect challenging. In this paper a buffer sizing approach is presented which exploits that FIFO buffers bound interference between tasks on shared processors. The approach combines temporal analysis using a cyclic dataflow model with computation of buffer capacities in an iterative manner and thereby enables higher throughput guarantees at smaller buffer capacities. It is shown that convergence of the proposed analysis flow is guaranteed. The benefits of the presented approach are demonstrated using a WLAN 802.11p transceiver application executed on a multiprocessor system with shared processors. If buffers without blocking writes are used an up to 25% higher guaranteeable throughput and up to 23% smaller buffer capacities can be determined compared to existing approaches. For systems using buffers with blocking writes the guaranteeable throughput is even up to 43% higher and buffer capacities up to 11% smaller.
机译:现有的用于实时流处理应用程序的时间分析和缓冲区大小调整技术忽略了FIFO缓冲区限制了同一处理器上的任务之间的干扰。通过考虑这种影响,可以表明缓冲区容量的减少会导致更高的吞吐量。但是,缓冲器容量和吞吐量之间的关系通常是非单调的,这使得对该效果的利用具有挑战性。在本文中,提出了一种缓冲区大小确定方法,该方法利用FIFO缓冲共享处理器上的任务之间的绑定干扰。该方法以迭代方式将使用循环数据流模型的时间分析与缓冲区容量的计算相结合,从而在较小的缓冲区容量下实现更高的吞吐量保证。结果表明,所提出的分析流程具有收敛性。通过在具有共享处理器的多处理器系统上执行的WLAN 802.11p收发器应用程序,演示了所提出方法的优势。如果使用没有阻塞写操作的缓冲区,则与现有方法相比,可以确定的吞吐量最多提高25%,缓冲区容量最多可以降低23%。对于使用带阻塞写入的缓冲区的系统,可保证的吞吐量甚至高出43%,而缓冲区容量则小11%。

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